Chalk of the Day, August 11: Shohei Ohtani to homer at +219

The chalkiest home run prop on the Tuesday board, checked against 5,000 play-by-play simulations of Kansas City at the Dodgers. The +219 price implies 31.3%. The simulations say 25.6%. Negative EV at about -18%; it becomes a play at +291 or longer.

Written by Jesse, NegativeEV. Last updated 11 August 2026.

• Sample: 5,000 pitch-by-pitch simulations of one game
• Window: 11 August 2026 slate
• Priced at: +219, read off the board before the game; the earlier snapshot across five books was +196
• Measured: 2026-08-11

Narration on the episode is synthetic, voiced from the written read; the analysis is the simulator's.

The bet

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Across 5,000 simulations Ohtani's average is 0.29 home runs and the median is zero: he fails to homer in about 74 of every 100 simulated games, and homers twice or more in about 3. The standard error on the simulated probability is 0.62 points, which puts the gap to the market at 13.3 standard errors. That is a statement about our own noise, not a proof the book is wrong.

This is the second day running that Ohtani has been the chalkiest home run prop on the board, and the second day running that the simulations have graded him Negative EV.

What works against him

His own recent form is the biggest thing pulling the number down, worth 3.3 points. That is the unusual part: the factor doing the damage is not the pitcher, it is Ohtani.

The shape of it is in the game log. He has 26 home runs in 471 plate appearances over 106 games this season, which is the profile the price is built on. Since the All-Star break he has 4 in 84 plate appearances across 20 games, and his most recent one was on 5 August, six days and 17 plate appearances ago. His strikeout rate over the last 14 days is 22.0%, against 23.6% for the season, so this is not a strikeout problem. It is exit velocity and launch angle drifting at the same time.

The matchup takes another 2.7 points off, through Michael Wacha's season form. Wacha is a right-hander, 2,163 pitches into the season and ranked against the 549 pitchers with 200 or more, and the striking thing about him is where the ball comes from: a 6.43-foot release height puts him in the 99.1st percentile, essentially the top of the league, thrown from an over-the-top slot with 6.72 feet of extension. Ohtani has never faced him — zero career plate appearances.

Being at home costs about a point. Ohtani is on the home side, so his last trip to the plate only happens if the game needs a bottom of the ninth. The simulations give him 4.46 trips on average, and that is the whole issue: at five at-bats this is close to a fair-value play, and at six it would be a good one.

What works for him

One thing, and it is a big one. Ohtani's own career profile as a hitter is worth 5.7 points over an average hitter — the largest single factor in either direction on the whole board today. His home run rate, exit velocity and launch angle are all elite, and the simulator knows it.

That is the entire bull case. The weather, the ballpark, the rest of the order and Wacha's pitch mix all nudge the number around, but they land inside the noise threshold, so we are not going to point at any of them and claim a direction. Of the 37 factors neutralised in the ablation, 17 have a direction we can stand behind.

The ballpark is worth naming only because people assume it matters here: UNIQLO Field at Dodger Stadium ranks 14th of 30 for home runs with a park factor of 1.07. Mildly helpful, and far too small to close a 5.7-point gap.

What this does and does not say

It says that at +219, this prop is priced for a version of Ohtani who is hitting the way he was in June, against a pitcher whose release point is at the very top of the league, in a game where he is likely to get four or five swings rather than six.

It does not say he will not homer. He homers in about a quarter of the simulated games, which is a lot — it is simply not 31.3% of them. The bet needs +291 before those two numbers meet.

One prop is one game, and one game is mostly variance. The reason to run 5,000 of them is to find out what the price would have to be before the bet made sense, not to predict the afternoon.

Method

The game is simulated pitch by pitch 5,000 times from the projected lineups, and the prop is graded on how often it lands. 37 factors were neutralized one at a time, each arm a separate re-run, so one-at-a-time swings do not sum to the projection; 17 of the 37 came back with a direction we can stand behind. The price is +219 as read off the board before the game, and an earlier snapshot across five books had it at +196 — the check is against the quoted price, rake included. This prop is quoted over-only, so there is no two-sided market to strip the book's rake out of, and some of the gap is the rake itself.

Written up for readers: https://negativeev.com/about/home-run-props All findings: https://negativeev.com/research